Methods and apparatus to count people in an audience

ABSTRACT

Methods, apparatus, systems and articles of manufacture to count people in an audience are disclosed. An example method includes analyzing location information collected by a portable device indicative of a location of the portable device. The method also includes analyzing proximity information collected by the portable device indicative of when a person is near the portable device. The example method further includes generating presence information based on (1) the location information and (2) the proximity information, the presence information being indicative of whether the person is present in a media exposure environment associated with a media presentation device.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience measurement, and, moreparticularly, to methods and apparatus to count people in an audience.

BACKGROUND

To identify audience compositions, an audience measurement entityenlists a plurality of people to cooperate as panelists in an audiencemeasurement panel. Media exposure and/or consumption habits of thepanelists and/or demographic data associated with the panelists iscollected and used to statistically project a size and demographicmakeup of, for example, a television viewing audience as a whole. Insome instances, automatic or passive measurement systems aresupplemented with active measurement system(s) that require, forexample, input from the panelists.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an example system constructed in accordance withteachings of this disclosure to monitor media.

FIG. 2 is a block diagram of an example implementation of the examplebase metering device of FIG. 1.

FIG. 3 is an example presence data structure associated with the examplebase metering device of FIGS. 1 and/or 2.

FIG. 4 is a block diagram of an example implementation of the exampleportable device of FIG. 1.

FIG. 5 is a block diagram of an example implementation of the examplepresence detector of FIGS. 2 and/or 4.

FIG. 6 is an example table including example presence data associatedwith the example presence detector of FIG. 5.

FIG. 7 is a flowchart representative of example machine readableinstructions that may be executed to implement the example base meteringdevice of FIGS. 1 and/or 2.

FIG. 8 is a flowchart representative of example machine readableinstructions that may be executed to implement the example portabledevice of FIGS. 1 and/or 4.

FIG. 9 is a flowchart representative of example machine readableinstructions that may be executed to implement the example presencedetector of FIG. 5.

FIG. 10 is a flowchart representative of example machine readableinstructions that may be executed to implement the example presencedetector of FIG. 5.

FIG. 11 is a block diagram of an example processor platform capable ofexecuting the example machine readable instructions of FIG. 7 toimplement the example base metering device of FIGS. 1 and/or 2, capableof executing the example machine readable instructions of FIG. 8 toimplement the example portable device of FIGS. 1 and/or 4, capable ofexecuting the machine readable instructions of FIG. 9 to implement theexample presence detector of FIG. 5, capable of executing the machinereadable instructions of FIG. 10 to implement the example presencedetector of FIG. 5.

DETAILED DESCRIPTION

The process of enlisting and retaining participants for purposes ofaudience measurement can be a difficult and costly aspect of theaudience measurement process. For example, participants must becarefully selected and screened for particular characteristics so thatthe population of participants is representative of the overall viewingpopulation. In addition, the participants must be willing to performspecific tasks that enable the collection of the data and, ideally, theparticipants selected must be diligent about performing these specifictasks so that the audience measurement data accurately reflects theirviewing habits.

For example, some audience measurement systems call for an amount ofon-going input from the panelist (e.g., an audience member being exposedto media via a television). In some examples, the input is provided bythe panelist physically engaging an input of a people meter. A peoplemeter is an electronic device that is typically disposed in a mediaaccess area (e.g., a viewing area such as a living room of a panelisthousehold) and that is proximate to and/or carried by one or morepanelists. In some instances, the people meter is adapted (e.g.,programmed) to communicate with a base metering device. The basemetering device, which is sometimes referred to as a site unit, measuresvarious signals associated with the monitored media presentation device(e.g., a television) for a variety of purposes including, for example,determining an operational status (e.g., on, off, standby, etc.) of themedia presentation device) and identifying the media being presented bythe media presentation device. Based on one or more triggers (e.g., achannel change or an elapsed period of time), the people meter generatesa prompt to request presence and/or identity information from theaudience. In some examples, the presence and/or identity information issupplied by depressing one of a set of buttons each of which is assignedto represent a different panelist (e.g., household member).

Periodically one or more persons (e.g., panelists and/or householdmember(s)) may forget or otherwise fail to log in via the people meterwhen they decide to, for example, consume media (e.g., watchtelevision). Additionally, one or more persons may forget or otherwisefail to log out of the people meter when they finish a media session(e.g., quit watching television) and exit the media exposure environmentwhile the media presentation device is still presenting media (e.g., toa person other than the person that left or to an empty room).Accordingly, the people meter prompts the corresponding panelists toregister (e.g., log in) or to indicate that the panelists are stillpresent (e.g., located in the media exposure area corresponding to themedia presentation device). The presence information collected by thepeople meter is referred to herein as “people meter data.”

Although periodically inputting information in response to a prompt maynot be burdensome when required for an hour, a day or even a week ortwo, some participants find the prompting and data input tasks to beintrusive and annoying over longer periods of time. As a result, in someinstances, panelists may choose to ignore prompts from the people meterand, thus, fail to provide accurate presence information. As such, thereis a need to reduce a frequency at which the panelists are promptedwhile gathering accurate presence information, especially when thepresence information is to be used in connection with detected mediabeing played on a media presentation device.

Example methods, apparatus, and/or articles of manufacture disclosedherein reduce a number of inaccurate measurements generated that resultfrom panelists failing to log in and/or log out when they begin and/orstop a media exposure session. In particular, examples disclosed hereinuse data collected via a portable secondary device (e.g., a smart phone,a tablet, a laptop computer, etc.) associated with (e.g., owned byand/or assigned to) a panelist to automatically detect the presence orabsence of the panelist and/or another person (e.g., another householdmember and/or a visitor) within a media exposure environment including aprimary media presentation device (e.g., a television located in aliving room).

In some disclosed examples, the portable device includes softwareprovided by a media measurement entity (e.g., the Nielsen Company, US(LLC)) to capture data via the portable device that can be analyzed todetermine a location of the portable device relative to, for example, anexposure area of a primary media presentation device and to detect aperson (e.g., the panelist associated with the portable device, anotherperson (also a panelist), and/or a visitor in the home) in proximity tothe portable device (e.g., within a threshold distance of the portabledevice). The data collected by the portable device to indicate thepresence of people, including location information and proximityinformation (e.g., whether one or more persons is near the portabledevice) is referred to herein as “secondary presence data” to indicatethe presence data is based on information collected via the portable(secondary) device as opposed to the device presenting the media (i.e.,the primary media presentation device). The presence information derivedfrom the portable device is referred to as “secondary” because presenceinformation is also collected by a primary people metering device suchas, for example, a base unit deployed as a stationary meter in the mediaexposure environment. The presence information collected by the primarypeople metering device is referred to herein as “primary presence data.”

Using location information (e.g., a coordinate based on a globalpositioning system (GPS)) generated by the portable device incombination with proximity information generated by the portable device(e.g., whether one or more persons is near the portable device), thepresence (or absence) of the person detected in proximity to a primarymedia presentation device may be determined. For example, if locationinformation (e.g., a GPS coordinate) from the portable device isindicative of the portable device being located away from a mediaexposure environment in which a primary media presentation is located(e.g., a living room of a residence of the panelist) and the proximityinformation (e.g., captured audio data such as a person's voice that isidentified as corresponding to the panelist via voice recognition)indicates the corresponding panelist is near the portable device, thepanelist cannot be present in the media exposure environment of theprimary media presentation device.

In some examples, location information collected via the portable deviceprovides finer granularity to determine that the portable device, and byimplication a person detected in proximity to the portable device, islocated in, for example, the house of the panelist but in a differentroom. In such examples, the person would again be considered absent fromthe media exposure environment of the primary media presentation device.In some examples, the location information collected via the portabledevice indicates that the portable device is co-located with the primarymedia presentation device (e.g., in the media exposure environment ofprimary presentation device) such that when a person is detected asbeing in proximity to the portable device based on the proximityinformation collected by the portable device, the person can beidentified as present in the media exposure environment. Thus, theperson detected as present constitutes an audience member of media beingpresented via the primary media presentation device.

The particular distance between a person and the portable device for theperson to be considered in proximity with the portable device dependsupon, for example, the location of the portable device and the type ofdata being analyzed to determine proximity of the person to the portabledevice. In some examples, the proximity determination is based on usagedata collected from the portable device. For example, certain usagecharacteristic(s) and/or value(s) imply that the person is holding theportable device and, thus, indicative of a high likelihood that theperson is near the portable device. Additionally or alternatively, theproximity determination is based on audio data and/or image datacaptured via one or more sensors of the portable device (e.g., amicrophone and/or a camera). In such examples, the person may bedetermined to be near the portable device but not actually carrying orholding the portable device.

Examples disclosed herein utilize the proximity determination incombination with location information indicative of a physical locationof the portable device. For example, if the location of the portabledevice is determined to be outside the media exposure environment of theprimary media presentation device (e.g., away from a room of house wherethe primary media presentation device is located), a person determinedto be near the portable device is likewise not present in the mediaexposure environment of the primary media presentation device.Accordingly, references to a person being detected “in proximity” to aportable device as used herein correspond to that person being detectedin the same location as the portable device. That is, if (1) theportable device is located outside of the media exposure environment ofthe primary media presentation device and (2) the proximity dataindicates that the corresponding person is sufficiently close (e.g.,within a threshold distance and determined with to a thresholdlikelihood or confidence) to the portable device, examples disclosedherein determine and/or confirm that the person is not located in themedia exposure environment. By contrast, if (1) the portable device islocated within the media exposure environment and (2) the proximity dataindicates that the corresponding person is sufficiently close to theportable device, examples disclosed herein determine and/or confirm thatthe person is located in the media exposure environment. As disclosedfurther below, additional or alternative presence determinations aremade by examples disclosed herein

In some examples disclosed herein, the secondary presence data (e.g.,presence determinations made by a secondary device based on the locationinformation of the portable (secondary) device and correspondingproximity data) is compared to the primary presence informationcollected by the base metering device. For example, the based meteringdevice prompts persons to log in via the people meter which has one ormore buttons to engage to indicate presence or absence from the mediaexposure environment. In some instances, the secondary presence dataindicates that a person is not present in the media exposure environmentof the primary media presentation device even though the person islogged in as an audience member via the people meter. In such instances,examples disclosed herein update and/or adjust the people meter data by,for example, removing the incorrectly counted audience member from oneor more counts and/or tallies associated with the media exposureenvironment and/or media detected in the environment. Additionally oralternatively, in some examples, the secondary presence data from theportable device indicates that a person who is not logged in via thepeople meter is, in fact, present in the media exposure environment ofthe primary presentation device. In such instances, examples disclosedherein update and/or adjust the people meter data by, for example,adding the incorrectly omitted audience member to one or more countsand/or tallies associated with the media exposure environment and/ormedia detected in the environment.

With the proliferation of portable electronic devices, it is becomingcommon for people to multitask or engage in activity on (or at least becarrying or otherwise in proximity to) a portable telephone or otherdevice such as a tablet (e.g., an iPad™) while being exposed to media(e.g., while watching television). Accordingly, as usage of portableelectronic devices continues to increase (e.g., while watchingtelevision), a greater reliance may be placed on the secondary presencedata collected from such devices as disclosed herein to supplementand/or confirm people meter data. In such instances, examples disclosedherein generate more accurate data and provide an ability to lessfrequently prompt people for input.

In some examples disclosed herein, the base metering device performs thecomparison(s) of the secondary presence data with the primary presencedata (e.g., people meter data) and the corresponding adjustment of databased on discrepancies. In some examples disclosed herein, the portabledevice communicates the collected secondary presence data (e.g.,location information and/or proximity information) to the base meteringdevice. Additionally or alternatively, the base metering device mayconvey the people meter data to the portable device to enable theportable device to perform one or more comparisons and/or anyappropriate changes to the people meter data. Additionally oralternatively, a central data collection facility collects the peoplemeter data from the base metering device and the secondary presence datafrom the portable device such that the central facility performs one ormore analyses and/or data updates and/or adjustments.

In some situations, such as when there is more than one member in apanelist household, detecting a person near a portable device may beinsufficient to specifically identify which household member is near theportable device. Accordingly, in some disclosed examples, the proximitydata collected by the portable device is further analyzed to identify orat least estimate the identity of the detected person. In some examples,estimating the identity of the person is based on a determination of aparticular demographic characteristic of the person. For example, theproximity data may include a photo of a person captured via a camera ofthe portable device. Based on an analysis of the photo (e.g., via facialrecognition), examples disclosed herein estimate that the person in theimage data is an adult male. In such examples, the identity of theperson detected near the portable device is associated with an adultmale panelist and/or household member. In some examples, where adetected person cannot be identified as corresponding to any knownpanelist and/or household member, examples disclosed herein determine orassume that the person is a visitor. In such instances, examplesdisclosed herein estimate one or more demographic characteristics of thevisitor based on, for example, the data collected by the portabledevice.

Additionally or alternatively, in some disclosed examples, data obtainedvia the portable device is analyzed to determine an activity or behaviorof one or more persons. For example, based on movement data collectedfrom motion sensors of the portable device, examples disclosed hereinestimate an activity and/or an amount of activity of the person.Further, in some examples disclosed herein, information regarding theusage of the portable device (e.g., applications on the device) iscollected by the portable device to be analyzed to determine a level ofengagement of the person to media being presented on the primary mediapresentation device. The additional data collected via the portabledevice (e.g., engagement information and/or activity information) isreferred to herein as “augmented audience data” because it providesadditional information that can augment or enhance audience measurementdata with additional (e.g., behavioral and/or engagement) informationabout the detected audience members and/or their viewing habits andbehaviors. For purposes of this disclosure, all data obtained via theportable device, including the secondary presence data (based onlocation information and proximity information), the augmented audiencedata (based on engagement information and activity information), and/orany other data collected by the portable device, is herein referred toas “secondary data.”

As can be seen from the foregoing, secondary data obtained via aportable device can significantly enhance audience measurement dataobtained via the people meter and/or base metering device. For example,the secondary data is used to detect people present in the environmentbut not logged in via the people meter. Additionally or alternatively,the secondary data is used to detect when a person is incorrectly loggedin as an audience member of the environment. Further, the secondary dataprovides additional or value-added information associated with detectedvisitors or guests by, for example, estimating demographic informationassociated with the visitors or guests. Further, the secondary data canaugment audience measurement data by providing an indication of not onlywho is watching but how they are watching, such as, what they are doingon the portable device (e.g., usage information), how that affects theirengagement, and/or how they are moving or behaving (e.g., activityinformation).

FIG. 1 illustrates an example house 100 having an example media exposureenvironment 102 including a primary media presentation device 104, aprimary people meter 112, and a base metering device 110. In the exampleof FIG. 1, the primary media presentation device 104 is a television.However, any suitable type of media presentation device (e.g., apersonal computer, a radio, etc.) may implement as the primary mediapresentation device 104 for the environment 102. In the illustratedexample of FIG. 1, the media exposure environment 102 is occupied by afirst person 120. A second person 122 is located outside the mediaexposure environment 102 (e.g., in a room of the house 100 in whichmedia presented via the media presentation device 104 cannot bedetected). In the example of FIG. 1, the first and second persons 120,122 are referred to as household members and/or panelists (e.g., membersof a “Nielsen family”) that have been statistically selected to develop,for example, media ratings data for a geographic location, a market,and/or a population/demographic of interest. In the illustrated example,one or more of the household members 120, 122 have registered with amedia measurement entity (e.g., by agreeing to be a panelist) and haveprovided their demographic information to the media measurement entityas part of a registration process to enable associating demographicswith, for example, detected media exposure. In the example of FIG. 1,the media exposure environment 102 includes an area in which the mediapresentation device 104 (e.g., a television) is located and from whichthe media presentation device 104 may be viewed and/or heard. Whetherany of the household members 120, 122 or other people (e.g., guests) arecounted as audience members of the media presentation device 104 dependson their presence within the media exposure environment 102. Forpurposes of this disclosure, a person that is within the media exposureenvironment 102 (and, thus, an audience member of media being presentedon the media presentation device 104) is referred to as “present.” Incontrast, a person that is not within the media exposure environment 102(and, thus, not an audience member of the media presentation device 104)is referred to as “absent.” For example, as illustrated in FIG. 1, thefirst person 120 within the media exposure environment 102 is presentand, therefore, is an audience member of the media presented via themedia presentation device 104. In contrast, the second person 122located outside of the media exposure environment 102 is absent and,thus, not an audience member of the media presentation device 104.

In the illustrated example of FIG. 1, the media presentation device 104is implemented by a television coupled to a set-top box (STB) thatimplements a digital video recorder (DVR) and/or a digital versatiledisc (DVD) player. Alternatively, the DVR and/or DVD player may beseparate from the STB. In some examples, the base metering device 110 ofFIG. 1 is installed (e.g., downloaded to and executed on) and/orotherwise integrated with the STB. Moreover, the example base meteringdevice 110 of FIG. 1 can be implemented in connection with additionaland/or alternative types of media presentation devices such as, forexample, a radio, a computer display, a video game console and/or anyother communication device able to present electronic media to one ormore individuals via any past, present or future device(s), medium(s),and/or protocol(s) (e.g., broadcast television, analog television,digital television, satellite broadcast, Internet, cable, etc.).Further, the example audience measurement system of FIG. 1 can beimplemented in additional and/or alternative types of environments suchas, for example, a room in a non-statistically selected household, atheater, a restaurant, a tavern, a store, an arena, etc.

The example base metering device 110 of FIG. 1 is configured as aprimarily stationary device disposed on or near the media presentationdevice 104 and may be adapted to perform one or more metering methods.Depending on the types of metering that the base metering device 110 isadapted to perform, the base metering device 110 may be physicallycoupled to the media presentation device 104 or may instead beconfigured to capture signals emitted externally by the mediapresentation device 104 such that direct physical coupling to the mediapresentation device 104 is not required. Preferably, an instance of thebase metering device 110 is provided for each media presentation device104 disposed in the house 100, such that the base metering devices 110may be adapted to capture data regarding all in-home media exposure. Insome examples, the base metering device 110 is implemented as a low-costelectronic device that may be shipped to the house 100 (e.g., viaregular mail) and easily installed by the panelist by, for example,plugging the base metering device 110 into a commercial power supply,(e.g., an electrical outlet. An example implementation of the basemetering device 110 of FIG. 1 is described in greater detail below inconnection with FIG. 2.

In the illustrated example, the primary people meter 112 is disposed inthe media exposure environment 102, within comfortable reach of thecorresponding person (e.g., the first person 120. Although the exampleprimary people meter 112 of FIG. 1 is illustrated as separate from theexample base metering device 110, the primary people meter 112 may beintegrated with the example base metering device 110. The exampleprimary people meter 112 of FIG. 1 has a set of inputs (e.g., buttons),each of which is assigned to represent a single, different panelistand/or household member. In some examples, the primary people meter 112includes additional buttons to identify the presence of guests orvisitors in the media exposure environment 102. In some examples, theprimary people meter 112 periodically presents a prompt via, forexample, a set of LEDs, a display screen, and/or an audible tone, torequest an indication from people that the people are present in themedia exposure environment 102 (e.g., by pressing an assigned buttonand/or depressing the button assigned to a person that is absent or nolonger in the media exposure environment).

In some examples, the primary people meter 112 is implemented as astand-alone device that is communicatively coupled to the base meteringdevice 110 and dedicating to people metering. In some examples, theprimary people meter 112 is an integral part of the base metering device110. In some examples, the primary people meter 112 is implemented as anintegral part of a remote control device to enable a user to interactwith the media presentation device 104. In some examples, the primarypeople meter 112 is implemented using a PDA or a cellular telephone thatis kept within comfortable arms reach of the viewers located in themedia exposure environment 102.

As shown in the illustrated example of FIG. 1, the first person 120 isnear (e.g., proximate to) a first portable device 114 and the secondperson 122 is near a second portable device 118. While the portabledevices 114, 118 are shown as being held by the first and second persons120, 122, respectively, a person may be considered in proximity to theportable device 114, 118 without holding, carrying, or otherwisedirectly interacting with the portable device 114, 118. For example, thefirst person 120 may put the first portable device 114 on a table. Insuch instances, the first portable device 114 may still be considered inproximity with first person 120 based on, for example, audio datacaptured by an audio sensor (e.g., a microphone) of the first portabledevice 114 and/or image data captured by an image sensor (e.g., acamera) of the first portable device 114.

The example portable devices 114, 118 are, for example, a cellulartelephone, a personal digital assistant (PDA), a smart phone, a handheldcomputer, a tablet, an e-reader, a laptop computer, and/or any othersuitable portable electronic device. Using a readily available and/orpanelist owned portable device to implement the portable devices 114,118 of FIG. 1 allows the persons 120, 122 to, for example, more easilyand more conveniently comply with terms of an agreement entered intowith a media measurement entity. Specifically, the person 120 mayalready have been carrying a smart phone on a regular basis beforebecoming a panelist such that carrying the portable device 114 does notplace any additional duties or burdens on the first person 120. In somesuch examples, the monitoring data obtained via the first portabledevice 114 is collected via software (e.g., program(s) running in abackground) executed on the first portable device 114. In some examples,the software is provided to the first portable device 114 by the mediameasurement entity via a download from a network, such as the Internet.In some examples, the software executing on the first portable device114 collects the monitoring data over time and transmits the collecteddata to a central data collection facility of the media measuremententity based on any suitable schedule and/or as needed. In someexamples, the base metering device 110 and/or the primary people meter112 periodically communicates control signals to the first portabledevice 114 instructing the first portable device 114 to capture peopledata (e.g., audio or image data). In such examples, the softwareinstalled on the first portable device 114 responds to the controlsignals by capturing the requested people data and transmitting thecaptured data back to the primary people meter 112.

In the example of FIG. 1, the portable devices 114, 118 are used todetermine the presence or absence of the corresponding persons 120, 122and/or other person(s) (e.g., one or more visitors) in the mediaexposure environment 102. In particular, presence data is gathered viaone or more sensors of the portable devices 114, 118 and/or one or moreprograms or applications executed on the portable devices 114, 118 as isdescribed in greater detail below. For example, the presence of thefirst person 120 is determined based on location information gathered bythe first portable device 114 in conjunction with proximity informationgathered by the first portable device 114 indicative of whether thefirst person 120 is near the first portable device 114. In someexamples, the location information associated with the first portabledevice 114 is to be ignored based on, for example, the proximityinformation indicating that the first person 120 is not near the firstportable device 114. That is, the presence of the first portable device114 in the media exposure environment 102 may be inconclusive evidenceof the presence of the first person 120 in the media exposureenvironment 102 because the first portable device 114 may have been leftby the first person 114 in the media exposure environment 102 when thefirst person left the environment 102. Accordingly, in some suchexamples, the data obtained from the location of the first portabledevice 114 is ignored as unreliable. However, in some examples, thelocation data of the first portable device 114 is still used to, forexample, generate one or more inferences about the presence or absenceof the first person 120 in the media exposure environment 102 (e.g.,near the media presentation device 104). For example, if the locationinformation of the first portable device 114 indicates that the firstportable device 114 is in transit outside of the house 100 (e.g., movingon a road or at a store as may be determined, for example, by a GPSmodule and/or speed sensors), it is inferred that the first person 120is carrying the first portable device 114, even when the first person isnot directly detected as being in proximity to the first portable device114. In some examples, the determination that the first portable device114 is in transit outside of the house is treated as confirmation thatthe first person 120 is absent from the media exposure environment 102.

In some examples, the first portable device 114 detects more than oneperson in proximity to the first portable device 114. In such examples,the proximity information used to detect people in proximity to thefirst portable device 114 is analyzed to distinguish and/or identifyeach of the detected people and/or to identify the number of peopledetected. In some examples, the first and second portable devices 114,118 are in the same vicinity such that each of the portable devices 114,118 separately detects the same person or people as being in proximityto each portable device 114, 118. In some such examples, the secondarydata collected by each portable device 114, 118 is compared and/orshared to assist in identifying detected person(s) and/or to avoidcounting the same person more than once. Such scenarios are described ingreater detail below.

In some examples, an identity of a person (e.g., the first person 120)detected as being in proximity to a portable device (e.g., the firstportable 114) corresponds to, for example, the owner or assigned user ofthe portable device. For example, the first portable device 114 mayidentify the first person 120 as the person near the first portabledevice 114. In some instances, the identity of a person detected asbeing near the first portable device 114 is assumed to be the firstperson 120. In other examples, the identity of the person detected asnear the first portable device 114 is not directly inferred or assumed.Accordingly, in some examples, the particular person and/or acharacteristic of the person may be identified or estimated based onfurther analysis of the proximity data (e.g., audio and/or image datacaptured by the first portable device 114). Additionally oralternatively, in some examples, the person detected as near the firstportable device 114 may not be identifiable because the person is not aregistered panelist (e.g., member of a household corresponding to thehouse 100), but rather is, for example, a visitor to the house 100. Insuch examples, one or more demographic characteristics (e.g., age,gender, ethnicity, etc.) of the detected visitor can be estimated basedon the data collected by the portable devices 114, 118.

Further, in some examples, data is collected via the portable devices114, 118 to augment audience measurement data with additionalinformation about detected persons. For example, the first portabledevice 114 gathers activity information based on, for example, datacaptured by one or more motion sensors of the first portable device 114indicative of an activity and/or behavior of the first person 120 (orany other person using the first portable device 120). In some examples,the first portable device 114 gathers usage information related toapplications being used on the first portable device 114 indicative of,for example, a level of engagement of the first person 120 (or any otherperson using the first portable device 114) with a media presentationplaying on the first portable device 114. Additionally or alternatively,the usage information associated with the first portable device 114 isused to determine a level of engagement with the media presentationdevice of the environment 102 and/or with the portable device itself.

In some examples, the first portable device 114 of FIG. 1 communicatesthe secondary data (e.g., proximity information, location information,activity information, engagement information, timestamp(s), etc.)obtained by the first portable device 114 to the example base meteringdevice 110 of FIG. 1. For example, the first portable device 114 of FIG.1 periodically and/or aperiodically transmits a message having a payloadof data to the base metering device 110. Additionally or alternatively,the example first portable device 114 of FIG. 1 transmits the data tothe base metering device 110 in response to queries from the basemetering device 110, which periodically and/or aperiodically polls theenvironment 102 for collected information from, for example, theportable devices 114, 118. In the illustrated example of FIG. 1, theexample base metering device 110 of FIG. 1 compares the primary presenceinformation received from the example primary people meter 112 of FIG. 1with the secondary presence data obtained via the example portabledevices 114, 118 to, for example, confirm the accuracy of the dataobtained via the primary people meter 112. In some examples, if there isa discrepancy between the primary presence information gathered via theexample primary people meter 112 and the secondary presence informationgathered via the portable devices 114, 118, the example base meteringdevice 110 of FIG. 1 adjusts the primary presence information byremoving incorrectly counted individuals from a tracked audience of themedia presentation device 104 and/or decreases a count or tally ofpeople in an audience for the media exposure environment 102.Alternatively, the example base metering device 110 of FIG. 1 adjuststhe primary presence information by adding individuals to the trackedaudience of the media presentation device 104 and/or increases a countor tally of people in an audience for the media exposure environment102.

In some examples, the base metering device 110 of FIG. 1 communicatesthe primary presence information generated via inputs from the exampleprimary people meter 112 to, for example, the first portable device 114.In such examples, the first portable device 114 compares the secondarypresence data gathered via the first portable device 114 with theprimary presence information gathered by the primary people meter 112 toconfirm or appropriately adjust the primary presence information. Whenthe primary presence information has been confirmed or adjusted asneeded, the data is sent to a central data collection facility in theillustrated example. The central facility uses the received data to, forexample, aggregate information associated with multiple panelisthouseholds and/or data collection devices or meters. Additionally oralternatively, the example base metering device 110 of FIG. 1 and one ormore of the portable devices 114, 118 separately communicate with thecentral data collection facility. In some such examples, the centraldata collection facility compares the primary presence informationgathered by the example primary people meter 112 and the secondarypresence data from the portable device(s) 114, 118 to, for example,adjust or confirm data indicative of the audience composition in themedia exposure environment 102 at a time corresponding to, for example,a detection of particular media being presented in the environment 102.

In some examples, the portable device(s) 114, 118 are additionally oralternatively tasked with detecting media presentations in the mediaexposure environment 102. For example, the first portable device 114 ofFIG. 1 includes one or more sensors (e.g., microphone(s) and/or imagecapturing devices) to collect and/or detect signatures, codes,watermarks, etc. indicative of media presented in the environment 102(e.g., by the media presentation device 104). In some examples, thefirst portable device 114 provides raw data collected by the sensor(s)of the first portable device 114 to the example base metering device 110for processing and identification of media. In some examples, the basemetering device 110 of FIG. 1 does not collect media identifyinginformation, but does collect people meter data indicative of a numberand/or identity of persons in the environment 102.

In some examples, the first portable device 114 of FIG. 1 functions as aprimary media presentation device to directly present media to which oneor more persons are exposed. In some such examples, the first portabledevice 114 of FIG. 1 detects the media playing on the first portabledevice 114. In such examples, the presence data collected by the firstportable device 114 is used to detect people near to tally or countpeople as audience members of the media playing on the first portabledevice 114. In some examples, the first portable device identifiesand/or estimates the identities of the detected people and/or, if thedetected people are not identifiable as panelists (e.g., non-panelistvisitors), estimates the demographic characteristics of the detectedpeople.

In some examples, the first portable device 114 functions as a secondscreen device playing media (e.g., content and/or advertisements)supplemental to media separately playing on, for example, the mediapresentation device 104. For example, while a media presentation isbeing played on the media presentation device 104, the first person 120may be viewing and/or interacting with supplemental media on the firstportable device 114. In some such examples, the first portable device114 monitors the media presentation of the media presentation device 104and the supplemental media being presented on the first portable device114. In some examples, the detected supplemental media and/or detectedinteractions with the supplemental media is analyzed to determine alevel of engagement of the first person 120 (e.g., with the primarymedia presentation device 104). In some examples, the supplemental mediamay be used to determine whether the first person 120 is properlycharacterized as an audience member of the media presentation playing onthe primary media presentation device 104 (e.g., according to theprimary people meter 112). For example, where the presence of the firstperson 120 in the media exposure environment 102 is uncertain based oninconclusive location information and/or proximity information, detectedinteraction with supplemental media on the first portable device 114corresponding to the media presentation playing on the mediapresentation device 104 is indicative of the first person 120 being anaudience member of the media presentation. In contrast, if mediadetected on the first portable device 114 is unrelated to the mediapresentation of the media presentation device 104, the first person 120is tracked as present but not engaged with the media presentation of themedia presentation device 104.

FIG. 2 illustrates an example implementation of the base metering device110 of FIG. 1. The example of FIG. 2 illustrates the base meteringdevice 110 implemented independent of the primary people meter 112.However, in other examples, the base metering device 110 and the primarypeople meter 112 are integrated together. The example base meteringdevice 110 of FIG. 2 includes a people analyzer 200 to develop audiencecomposition information regarding, for example, presence of people inthe media exposure environment 102 of FIG. 1. In the illustrated exampleof FIG. 2, the people analyzer 200 receives the primary presenceinformation from the primary people meter 112 through which persons(e.g., the first and/or second persons 120, 122) indicate presence inthe environment 102 by, for example, pushing a corresponding button onthe primary people meter 112. In some examples, the primary people meter112 only captures data and/or prompts for input when the primary mediapresentation device 104 is in an “on” state and/or when media isdetected as being presented in the environment 102.

In the illustrated example of FIG. 2, the people analyzer 200 includes apresence detector 212 to identify people in the environment 102 and/orto generate a people count. In the illustrated example, the peopleanalyzer 200 includes a presence table 210 to track the informationgenerated by the example presence detector 212. In the illustratedexample, the example people analyzer 200 of FIG. 2 generates peoplecounts or tallies corresponding to periods of time and/or in response toa detected change in the primary presence data collected via the primarypeople meter 112. In the illustrated example of FIG. 2, the examplepresence detector 212 receives the secondary presence data gathered viathe portable devices 114, 118. As described above, the secondarypresence data is indicative of the location of the portable devices 114,118 and person(s) being near the portable devices 114, 118. The examplepresence detector 212 of FIG. 2 analyzes and/or processes the secondarypresence data to, for example, determine presence of people (e.g., thefirst person 120) in the media exposure environment 102 of FIG. 1. Inthe illustrated example of FIG. 2, the presence detector 212 comparesthe primary presence data from the primary people meter 112 to thesecondary presence data from the portable device 114, 118 to confirm thepresence of, the first person 120 as logged in via the primary peoplemeter 112 and/or to identify discrepancies between the primary presencedata and the secondary presence data. Where there are discrepancies, theexample presence detector 212 of FIG. 2 adjusts or updates the primarypresence information collected by the people meter 112 (e.g., as storedin the presence table 210). In some examples, the comparison between theprimary presence information and the secondary presence informationdepends upon specifically identifying the person detected (e.g., whenthere are multiple household members). As such, in some examples, thepresence detector 212 of FIG. 2 analyzes the proximity information ofthe secondary presence data to specifically identify or estimate theidentity of a person that is detected as being near the portable device114, 118. Where the detected person cannot be positively identified(e.g., the person is a visitor in the house 100 or the data is notsufficient to identify the person with a threshold amount ofconfidence), the example presence detector 212 of FIG. 2 determines orat least estimates an identifying characteristic, such as a demographiccharacteristic (e.g., age, gender, etc.), of the detected person.

Further, in some examples, the example presence detector 212 of FIG. 2receives augmented audience data gathered via the portable devices 114,118 including activity information (e.g., based on motions sensors ofthe portable devices 114, 118) and/or engagement information (e.g.,based on usage of applications being used on the portable devices 114,118). In some examples, the example presence detector 212 of FIG. 2analyzes the activity information to determine the activity and/orbehavior of the detected person during, for example, a mediapresentation playing on the primary media presentation device 104.Additionally or alternatively, in some examples, the presence detector212 of FIG. 2 analyzes the engagement information to determine a levelof engagement of a detected person with, for example, a mediapresentation playing on the media presentation device 104. An exampleimplementation of the presence detector 212 is shown and described ingreater detail below in connection with FIG. 5.

In some examples, the people analyzer 200 includes a secondary datacoordinator 213 to coordinate the collection of data from the portabledevices 114, 118. In some examples, the secondary data coordinator 213periodically or aperiodically transmits a control signal to the portabledevice 114 and/or other portable devices that are present within theexposure environment 102 and/or within a communication range of the basemetering device 110. In some such examples, the portable device 114 isprogrammed to capture secondary data including secondary presence datain response to the control signal and transmit the collected data backto the base metering device 110. In some examples, the portable device114 only captures secondary data (e.g., audio data, image data,application usage data, etc.) when requested via the secondary datacoordinator 213. In other examples, the portable device 114 collectssecondary data and stores the data automatically but only transmits thedata to the base metering device 110 when requested by the base meteringdevice 110. In this manner, the secondary data coordinator 213 of thebase metering device 110 can control or coordinate when data is capturedand/or collected by the portable device 114.

For example, the secondary data coordinator 213 of the base meteringdevice 110 may detect the presence of the first person 120 within themedia exposure environment 102 based on the person manually logging invia the primary people meter 112. After a threshold period of time(e.g., 15 minutes), the base metering device 110 and/or the people meter112 may prompt the person 120 to confirm they are still present withinthe environment 120. However, in some examples, rather than promptingthe person 120 via the base metering device 110 and/or the people meter112, the secondary data coordinator 213 may send out a control signal towake up the portable device 114 with a request for the portable device114 to capture secondary data at that time. In some examples, theportable device 114 responds to the request by collecting secondary dataand transmitting the information back to the base metering device 110for analysis by the presence detector 212. In some examples, if thesecondary presence data confirms that the first person 120 is stillpresent within the media exposure environment 102, the base meteringdevice 110 will forego prompting the person 120 to re-register via thepeople meter 112. In this manner, the frequency of prompts and theassociated annoyance to panelists may be reduced. If the collectedsecondary presence data indicates that the person 120 has left theenvironment 102 (or is at least not detected by the portable device114), the base metering device 110 will prompt the first person tore-register via the people meter 112 to confirm whether the person 120is still present or has in fact left. In some examples, if the secondarydata provides a sufficient level of confidence to confirm the absence ofthe person 120, the base metering device 110 will automatically updatethe presence table 210 without prompting for any additional input viathe people meter 112.

Additionally or alternative, in some examples, the secondary datacoordinator 213 will send a control signal to the portable device when achange in audience membership is indicated via the people meter 112. Forexample, if the second person 122 enters the media environment 102 andlogs into the primary people meter 112, the secondary data coordinator213 of the base metering device 110 may transmit a request to wake upand/or collect secondary data from the portable devices 114, 118. Inthis manner, the base metering device may verify or determine whetherother people (e.g., other household members, visitors, etc.) haveentered the environment 102 with the second person 122. Furthermore, insuch examples, the base metering device can confirm the location of theportable devices 114, 118 within the media exposure environment 102 and,thus, identify the portable devices 114, 118 as available sources ofinformation regarding the presence of people within the media exposureenvironment 102. Further still, in addition to or instead oftransmitting control signals when the people meter 112 receives new dataor when a new prompt via the people meter 112 is due, the secondary datacoordinator 213 may transmit control signals at any other appropriatetime to control and/or coordinate when data is captured by the portabledevices 114, 118 and analyzed to verify and/or adjust the primarypresence data obtained via the primary people meter 112.

Although the people analyzer 200 is described above as being implementedvia the base metering device 110, in some examples, the people analyzer200 or components thereof is implemented via the people meter 112. Insome examples, the people meter 112 may include the secondary datacoordinator 213 to control when the portable device 114 is instructed tocapture secondary data. In some such examples, the secondary datacollected via the portable device 114 is transmitted to the primarypeople meter 112 and subsequently provided to the base metering device110 along with the primary presence information collected via manualinputs directly into the people meter 112. In some examples, the peoplemeter 112 generates the presence table 210 and/or analyzes the secondarydata and compares the data against the presence table 210 beforetransmitting the same to the base metering device 110.

Data generated by the example presence detector 212 of FIG. 2 is trackedin the example presence table 210. The table 210 and/or its data isstored in memory 208 of the example base metering device 110 of FIG. 2.The example memory 208 of FIG. 2 may include a volatile memory (e.g.,Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random AccessMemory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM, etc.) and/ora non-volatile memory (e.g., flash memory). The example memory 208 ofFIG. 2 may include one or more double data rate (DDR) memories, such asDDR, DDR2, DDR3, mobile DDR (mDDR), etc. The example memory 208 of FIG.2 may also include one or more mass storage devices such as, forexample, hard drive disk(s), compact disk drive(s), digital versatiledisk drive(s), etc.

The example time stamper 206 of FIG. 2 receives data from the examplepresence detector 212 and an example media detector 202 of the examplebase metering device 110 of FIG. 2. The example media detector 202 ofFIG. 2 detects presentation(s) of media in the media exposureenvironment 102 and/or collects identification information associatedwith the detected presentation(s). For example, the media detector 202,which may be in wired and/or wireless communication with the mediapresentation device 104, an STB associated with the media presentationdevice 104, and/or any other component of FIG. 1, can identify apresentation time and/or a source (e.g., the STB, a video game console,a DVR, etc.) of a media presentation. The presentation time and thesource identification data may be utilized to facilitate identificationof the media by, for example, cross-referencing a program guideconfigured, for example, as a look up table. In such instances, thesource identification data is, for example, the identity of a channel(e.g., obtained by monitoring a tuner of an STB or a digital selectionmade via a remote control signal) currently being presented on the mediapresentation device 104.

Additionally or alternatively, the example media detector 202 of FIG. 2can identify the media being presented by detecting codes (e.g.,watermarks) embedded with or otherwise conveyed (e.g., broadcast) withmedia being presented via the STB and/or the media presentation device104. As used herein, a code is an identifier that is transmitted withthe media for the purpose of identifying and/or for tuning to (e.g., apacket identifier header and/or other data used to tune or selectpackets in a multiplexed stream of packets) the corresponding media.Codes may be carried in the audio, in the video, in metadata, in avertical blanking interval, in a program guide, in content data, or inany other portion of the media and/or the signal carrying the media. Inthe illustrated example, the media detector 202 extracts the code(s)from the media. In other examples, the media detector 202 may collectsamples of the media and export the samples to a remote site fordetection of the code(s).

Additionally or alternatively, the example media detector 202 of FIG. 2can collect a signature representative of a portion of the media. Asused herein, a signature is a representation of a characteristic of thesignal carrying or representing one or more aspects of the media (e.g.,a frequency spectrum of an audio signal). Signatures may be thought ofas fingerprints of the media. Collected signature(s) can be comparedagainst a collection of reference signatures of known media (e.g.,content and/or advertisements) to identify media. In some examples, thesignature(s) are generated by the media detector 202. Additionally oralternatively, the example media detector 202 collects samples of themedia and exports the samples to a remote site for generation of thesignature(s). In the example of FIG. 2, irrespective of the manner inwhich the media of the presentation is identified (e.g., based on tuningdata, metadata, codes, watermarks, and/or signatures), the mediaidentification information is time stamped by the time stamper 206 andstored in the memory 208.

In the illustrated example of FIG. 2, an output device 214 periodicallyand/or aperiodically exports data (e.g., the data in the presence table210, media identifying information from the media detector 202) from thememory 208 to a data collection facility 216 via a network (e.g., alocal-area network, a wide-area network, a metropolitan-area network,the Internet, a digital subscriber line (DSL) network, a cable network,a power line network, a wireless communication network, a wirelessmobile phone network, a Wi-Fi network, etc.). In the illustrated exampleof FIG. 2, the data collection facility 216 is managed and/or owned byan audience measurement entity (e.g., The Nielsen Company (US), LLC).The audience measurement entity associated with the example datacollection facility 216 of FIG. 2 utilizes the people tallies generatedby the people analyzer 200 in conjunction with the media identifyingdata collected by the media detector 202 to generate exposureinformation. The information from many panelist locations may becollected and analyzed to generate ratings representative of mediaexposure by one or more populations of interest using any statisticalmethodology.

While an example manner of implementing the base metering device 110 ofFIG. 1 is illustrated in FIG. 2, one or more of the elements, processesand/or devices illustrated in FIG. 2 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example people analyzer 200, the example media detector202, the example presence detector 212, the example time stamper 206and/or, more generally, the example base metering device 110 of FIG. 2may be implemented by hardware, software, firmware and/or anycombination of hardware, software and/or firmware. Thus, for example,any of the example people analyzer 200, the example media detector 202,the example presence detector 212, the example time stamper 206 and/or,more generally, the example base metering device 110 could beimplemented by one or more analog or digital circuit(s), logic circuits,programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example peopleanalyzer 200, the example media detector 202, the example presencedetector 212, the example time stamper 206 and/or, more generally, theexample base metering device 110 of FIG. 2 is/are hereby expresslydefined to include a tangible computer readable storage device orstorage disk such as a memory, a digital versatile disk (DVD), a compactdisk (CD), a Blu-ray disk, etc. storing the software and/or firmware.Further still, the example base metering device 110 of FIG. 2 mayinclude one or more elements, processes and/or devices in addition to,or instead of, those illustrated in FIG. 2, and/or may include more thanone of any or all of the illustrated elements, processes and devices.

FIG. 3 illustrates an example instance of the example presence table 210of FIG. 2. In the illustrated example of FIG. 3, a first column 302 inthe table 210 includes rows 304, 306, 308 corresponding to individualpanelists associated with, for example, the house 100 of FIG. 1 (e.g.,the first and second persons 120, 122). The first column 302 of theexample presence table 210 includes one or more additional rows 310corresponding to guests or visitors detected in the media exposureenvironment 102. In the illustrated example of FIG. 3, the presencetable 210 includes a second column 312 to store the presence status ofeach of the panelists and/or guest(s) based on whether they registered(e.g., logged in) via the primary people meter 112. In the illustratedexample of FIG. 3, a logical high or ‘1’ in the second column 312indicates the corresponding panelist is present in the media exposureenvironment 102 and, thus, counted as an audience member. A logical lowor ‘0’ in the second column 312 indicates the corresponding panelist isabsent from the media exposure environment 102.

In the illustrated example of FIG. 3, the presence table 210 includes atally or count 314 that stores a total number of people present in themedia exposure environment 102. For example, as illustrated in FIG. 3,the first and second persons 120, 122 (corresponding to the first tworows 304, 306 of the example table 210) are indicated as present by theprimary people meter 112 while a third person (e.g., a panelist trackedin the third row 308) is indicated as being absent. Further, in theillustrated example, no guests (the fourth row 310) are present.Accordingly, the total count 314 of people based on the primary presenceinformation gathered by the primary people meter 112 is two (2). In someexamples, the presence table 210 contains additional rows correspondingto other panelists and/or additional guest slots. As described in detailbelow, the information tracked in the presence table 210 is confirmedand/or adjusted according to the secondary presence information providedby one or more of the portable devices 114, 118.

FIG. 4 illustrates an example implementation of the first portabledevice 114 of FIG. 1. The second portable device 118 of FIG. 1 mayadditionally or alternatively be implemented by the example of FIG. 4.In the illustrated example of FIG. 4, the portable device 114 includes amedia detector 434 to collect information identifying media in a similarmanner as the media detector 202 of FIG. 2 described above. In someexamples, the media detector 434 collects information regarding mediabeing viewed on the portable device 114 regardless of the source of themedia (e.g., irrespective of whether the media is being played on, forexample, the primary media presentation device 104 or on the portabledevice 114 itself (e.g., when the portable device 114 functions as aprimary media presentation device)). In some examples, the mediadetector 434 of FIG. 4 additionally or alternatively collectsinformation regarding supplemental media being viewed on the firstportable device 114 (e.g., when the first portable device 114 functionsas a second screen device). Data collected by the example media detector434 of FIG. 4 is stored in memory 414 of the first portable device 114.

The example portable device 114 of FIG. 4 includes a secondary datagenerator 400 to generate data regarding, for example, the presence orabsence of people in the example media exposure environment 102 of FIG.1 (e.g., secondary presence data) and/or information about the behavior,activity, and/or engagement of a person present in the media exposureenvironment 102 (e.g., augmented audience data). In the illustratedexample, the secondary data generator 400 includes an example locationinformation generator 402, an example proximity information generator404, an example activity information generator 406, an exampleengagement information generator 408, an example time stamper 410, andan example presence detector 412.

In some examples, an audience measurement entity provides the secondarydata generator 400 to the portable device 114 by, for example, makingthe secondary data generator 400 available for download over a networkand/or installing the secondary data generator 400 on the portabledevice 114. In some examples, the secondary data generator 400 issoftware installed on the portable device 114 that runs in thebackground to passively collect and generate the secondary data usingone or more automated techniques as described below

The example location information generator 402 of FIG. 4 generateslocation information using data from one or more sensors and/ordetectors of the example portable device 114. For example, the locationinformation generator 402 utilizes course location data obtained from aglobal positioning system (GPS) module 416. In some examples, thelocation information generator 402 of FIG. 4 includes a wireless signalstrength detector 418 to provide location information. For example, thewireless signal strength detector 418 of FIG. 4 detects a value orstrength of a wireless signal (e.g., WiFi and/or Bluetooth) received bythe example portable device 114 from one or more other wireless devicesin the household 100 of FIG. 1. For example, the wireless signalstrength detector measures data associated with a wireless communicationbetween the portable device 114 and the primary media presentationdevice 104 and/or a wireless communication between the portable device114 and the example base metering device 110. In some examples, thewireless signal strength detector 418 generates location informationbased on a positional relationship of the portable device 114 relativeto other wireless devices (e.g., a personal computer, a wireless router,the primary media presentation device 104, the base metering device 110,etc.). In some examples, panelists such as the first and second persons120, 122 provide a listing of all wireless (Wi-Fi, Bluetooth) devicesassociated with a wireless network in the house 100 that may be storedand/or accessed by the wireless signal strength detector 418. In thismanner, the example location information generator 402 utilizes thewireless signal strength detector 418 to identify a specific location ofthe portable device 114 within the house 100 (e.g., whether the portabledevice is in the same room as the primary media presentation device104). Additionally or alternatively, the example location informationgenerator 402 of FIG. 4 uses data collected from an audio sensor 420(e.g., a microphone) of the portable device 114 to determine a locationof the portable device 114. For example, the audio sensor 420 maycapture audio signals generated by the primary media presentation device104, which are recognized as generated by the primary media presentationdevice 104 based on, for example, audio codes (e.g., watermarks) in theaudio signal. In some examples, the example location informationgenerator 402 infers that the portable device 114 is in the mediaexposure environment 102 based on the clarity and/or strength (e.g.,loudness) of the audio signal. The example location informationgenerator 402 of FIG. 4 outputs location information corresponding tothe location of the portable device 114 to the time stamper 410 and/orstored in the memory 414.

The example proximity information generator 404 of FIG. 4 generatesproximity information using data from one or more sensors and/ordetectors of the portable device 114 indicative of the proximity of aperson (e.g., the first and/or second persons 120, 122 and/or a visitorto the house 100) to the portable device 114. For example, the proximityinformation generator 404 of FIG. 4 generates proximity data based ondata captured via the audio sensor 420. For example, the proximityinformation generator 404 of FIG. 4 uses the audio sensor 420 to capturesounds produced by people (e.g., talking), thereby detecting when atleast one person is near (e.g., within a threshold distance of) theportable device 114. In some examples, the proximity informationgenerator 404 of FIG. 4 generates proximity data based on images and/orvideo captured by a camera 424 of the portable device 114. In someexamples, the proximity information generator 404 of FIG. 4 generatesproximity data based on a fingerprint reader 426. In some examples, theproximity information generator 404 generates proximity informationbased on usage of the portable device 114 (e.g., usage of applicationsrunning on the portable device 114) detected via an application usagedetector 428. In some examples, the mere fact that the portable device114 is being used is indicative that a person is in proximity to theportable device 114 because the person is using the device.

The example proximity information generator 404 of FIG. 4 outputs data(e.g., proximity information) to the example time stamper 410 to be timestamped in a manner similar to the location information generated by theexample location information generator 402. In the illustrated example,the location information from the example location information generator402 of FIG. 4 and the proximity information from the example proximityinformation generator 404 of FIG. 4 comprises the secondary presencedata that is transmitted to the example base metering device 110 ofFIGS. 1 and/or 2 for analysis via, for example, the presence detector212 of the base metering device 110 as described above in connectionwith FIG. 2.

The example activity information generator 406 of FIG. 4 generatesactivity or behavior information based on, for example, data collectedfrom one or more motion sensors 430 (e.g., accelerometer, magnetometer,etc.) of the portable device 114. In some examples, activity and/ormotion sensing information is analyzed by the activity informationgenerator 406 to determine how the portable device 114 is being handledto infer an activity or behavior of the person using the portable device114. In some examples, the activity information generator 406 of FIG. 4provides the activity information to the time stamper 410 to be timestamped and stored in the memory 414.

The example engagement information generator 408 of FIG. 4 determines alevel of engagement of a person (e.g., the first person 120) with mediabeing played on, for example, the primary media presentation device 104.For example, the engagement information generator 408 of FIG. 4generates data based on usage of the portable device 144 (e.g., usage ofapplications running on the portable device 114) via an applicationusage detector 432. In some examples, the application usage detector 432of FIG. 4 is the same as the application usage detector 428 of theproximity information generator 404. However, while the exampleapplication usage detector 428 of the proximity information generator404 tracks whether applications are being used, the example applicationusage detector 432 of the engagement information generator 408 monitorshow applications are being used and what media and/or subject matter isassociated with the applications. For example, if a web browser is beingused on the portable device 114, the example application usage detector428 of the proximity information generator 404 records the usage toindicate that a person was using the portable device 114 and, therefore,was in proximity with the portable device 114. In contrast, the exampleapplication usage detector 432 of the engagement information generator408 of the illustrated example records the media associated with awebsite being visited via the web browser. If the websites is associatedwith media currently being presented on the primary media presentationdevice 104 when a person is present in the media exposure environment102, then a relatively high level of engagement with the media playingon the primary media presentation device 104 is inferred by the exampleengagement information generator 408. If, on the other hand, the visitedwebsite is unrelated to the media playing on the primary mediapresentation device 104, a relatively low level of engagement with themedia playing on the primary media presentation device 104 is inferredby the example engagement information generator 408. In some examples,the application usage detector 432 of FIG. 4 operates in connection withthe example media detector 434 of FIG. 4 to compare primary mediaplaying on a primary media presentation device 104 (e.g., a television)with supplemental media accessed via the portable device 114. In someexamples, rather than determining a level or degree of engagement of aperson with the primary media, the comparison results are used todetermine whether the person is to be counted as present in the mediaexposure environment 102 for purposes of rating the media playing on theprimary media presentation device 104. For example, if the supplementalmedia is related to the primary media, the person may be identified aspresent. However, if the supplemental media is unrelated to the primarymedia, the person may be omitted from a list of present people.

As another example, the example application usage detector 432 of theengagement information generator 408 tracks social media applicationusage. For example, the application usage detector 432 of the engagementinformation generator 408 collects comments, tweets, posts, etc., madeto, for example, one or more social networking sites and/orapplications. In such examples, the content and/or subject matter of thecomments, tweets, posts, etc., is analyzed and compared to the mediaand/or subject matter of a media presentation being played on theprimary media presentation device 104 at a corresponding time. As such,in some examples, the engagement information generator 408 of FIG. 4provides the collected engagement information to the time stamper 410 tobe time stamped and stored in the memory 414. The activity informationcollected by the example activity information generator 406 and/or theengagement information collected by the example engagement informationgenerator 408 form augmented audience data that is transmitted to theexample base metering device 110 for analysis via, for example, thepresence detector 212 as described above in FIG. 2.

In some examples, the secondary data generator 400 of FIG. 4 includes apresence detector 412. In some examples, the presence detector 412 ofFIG. 4 operates in a similar manner as the presence detector 212 of FIG.2. That is, in some examples, the presence detector 412 of FIG. 4analyzes the presence information (e.g., the location informationgenerated by the location information generator 402 and/or the proximityinformation generated by the proximity information generator 404)obtained from the portable device 114 to determine presence informationfor a person in the media exposure environment 102 of FIG. 1. Further,in some examples, the presence detector 412 of FIG. 4 compares theanalyzed presence information to the primary presence data obtained bythe primary people meter 112 (e.g., as represented in the presence table210) received from the example base metering device 110 to eitherconfirm the presence of persons logged in via the primary people meter112 or to account for discrepancies between the primary presenceinformation and the secondary presence information. Accordingly, in suchexamples, the example base metering device 110 transmits the primarypresence data to the secondary data generator 400 of the portable device114 in addition to or in lieu of the portable device 114 transmittingthe secondary presence data to the example base metering device 110.

Additionally, as described for the presence detector 212 of FIG. 2, insome examples, the presence detector 412 of FIG. 4 analyzes the datafrom one or more sensors (e.g., the audio sensor 420 and/or the camera424) to identify or estimate the identity of a person that is detectedas being near the portable device 114. Additionally or alternatively,the presence detector 412 of FIG. 4 identifies or estimates ademographic characteristic of the detected person. Further, in someexamples, the presence detector 412 of FIG. 4 analyzes the engagementinformation to determine a level of engagement of a detected person withmedia presented on the primary media presentation device 104. Further,in some examples, the presence detector 412 of FIG. 4 analyzes theactivity information to determine the activity or behavior of thedetected person during a media presentation playing on the primary mediapresentation device 104. The example presence detector 412 of FIG. 4 isdescribed in greater detail below in connection with FIG. 5.

The example memory 414 of FIG. 4 may be a native memory provided on theportable device 114. The example memory 414 may include a volatilememory (e.g., Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM,etc.) and/or a non-volatile memory (e.g., flash memory). The examplememory 414 of FIG. 4 may also include one or more mass storage devicessuch as, for example, hard drive disk(s), compact disk drive(s), digitalversatile disk drive(s), etc.

In the illustrated example of FIG. 4, an output device 436 periodicallyand/or aperiodically exports data from the memory 414 to the datacollection facility 216 via a network (e.g., a local-area network, awide-area network, a metropolitan-area network, the Internet, a digitalsubscriber line (DSL) network, a cable network, a power line network, awireless communication network, a wireless mobile phone network, a Wi-Finetwork, etc.). In some examples, the network through which the basemetering device 110 communicates with the data collection facility 216is the same as the network used by the portable device 114.

While an example manner of implementing the first portable device 114 ofFIG. 1 and/or the second portable device 118 of FIG. 1 is illustrated inFIG. 4, one or more of the elements, processes and/or devicesillustrated in FIG. 4 may be combined, divided, re-arranged, omitted,eliminated and/or implemented in any other way. Further, the examplesecondary data generator 400, the example location information generator402, the example GPS module 416, the example wireless signal strengthdetector 418, the example proximity information generator 404, theexample application usage detector 428, the example engagementinformation generator 408, the example application usage detector 432,the example activity information generator 406, the example time stamper410, the example presence detector 412, the example media detector 434and/or, more generally, the example portable device 114 of FIG. 4 may beimplemented by hardware, software, firmware and/or any combination ofhardware, software and/or firmware. Thus, for example, any of theexample secondary data generator 400, the example location informationgenerator 402, the example GPS module 416, the example wireless signalstrength detector 418, the example proximity information generator 404,the example application usage detector 428, the example engagementinformation generator 408, the example application usage detector 432,the example activity information generator 406, the example time stamper410, the example presence detector 412, the example media detector 434and/or, more generally, the example portable device 114 of FIG. 4 couldbe implemented by one or more analog or digital circuit(s), logiccircuits, programmable processor(s), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example secondarydata generator 400, the example location information generator 402, theexample GPS module 416, the example wireless signal strength detector418, the example proximity information generator 404, the exampleapplication usage detector 428, the example engagement informationgenerator 408, the example application usage detector 432, the exampleactivity information generator 406, the example time stamper 410, theexample presence detector 412, the example media detector 434 and/or,more generally, the example portable device 114 of FIG. 4 is/are herebyexpressly defined to include a tangible computer readable storage deviceor storage disk such as a memory, a digital versatile disk (DVD), acompact disk (CD), a Blu-ray disk, etc. storing the software and/orfirmware. Further still, the example portable device 114 of FIG. 4 mayinclude one or more elements, processes and/or devices in addition to,or instead of, those illustrated in FIG. 4, and/or may include more thanone of any or all of the illustrated elements, processes and devices.

FIG. 5 illustrates an example implementation of the example presencedetector 212 of the example base metering device 110 of FIG. 2. Theexample of FIG. 5 may additionally or alternatively be used to implementthe presence detector 412 of the portable device 114 of FIG. 4.Additionally or alternatively, the example presence detector 212 of FIG.5 may be implemented at the example data collection facility 216 ofFIGS. 2 and/or 4. In such examples, the base metering device 110communicates the primary presence data to the data collection facility216 and the portable device 114 communicates the secondary presence datato the data collection facility 216.

The example presence detector 212 of FIG. 5 includes a locationdeterminer 502, a proximity determiner 504, an identity estimator 506, acharacteristic estimator 508, a presence data comparator 510, anactivity determiner 512, and an engagement determiner 514. The examplelocation determiner 502 of FIG. 5 determines a location of the portabledevice 114 based on data provided by the example location informationgenerator 402 of the portable device 114 of FIG. 4. In some examples,the location determiner 502 of FIG. 5 determines the location of theportable device 114 relative to the media exposure environment 102. Thatis, the example location determiner 502 of FIG. 5 determines whether theportable device 114 is in an area of exposure of the primary mediapresentation device 104 (e.g., the media exposure environment 102) oroutside the area of exposure using data collected by the portable device114. In some examples, course location information, such as coordinatesobtained via the GPS module 416 of the location information generator402, is sufficient to make this determination. For example, if GPSlocation data indicates that the portable device 114 is two miles awayfrom the house 100, the example location determiner 502 of FIG. 5determines that the portable device 114 is not located in the mediaexposure environment 102. However, if GPS location data indicates theportable device is at the house 100, supplemental location informationof a finer granularity is used by the example location determiner 502 tospecifically locate the portable device 114 in the room including theprimary media presentation device 104. Accordingly, in some examples,GPS location data is supplemented with, for example, wireless signalstrength information detected by the example wireless signal strengthdetector 418 and/or audio signals captured by the example audio sensor420 to determine whether the portable device 114 is located in the sameroom as the primary media presentation device 104 (e.g., in the mediaexposure environment 102) or located somewhere else in the house 100.

The example proximity determiner 504 of FIG. 5 determines whether aperson is in proximity to the portable device 114 based on, for example,an analysis of audio data captured by the audio sensor 420 of theportable device 114. For example, if the audio sensor 420 detects avoice of a person near the portable device 114, the example proximitydeterminer 504 of FIG. 5 determines that a person is near the portabledevice 114. In some examples, the proximity determiner 504 determinesthat a person is near the portable device 114 based on image data (e.g.,a picture or video, a reflected glow, etc.) captured via the camera 424of the portable device 114. In some examples, the proximity determiner504 of FIG. 5 determines proximity based on feedback from thefingerprint reader 426 of the portable device 114. Additionally oralternatively, in some examples, the proximity determiner 504 of FIG. 5determines proximity based on usage information collected by theapplication usage detector 428 of the portable device 114.

The determination of whether a person is near the portable device 114 inconjunction with the determination of the location of the portabledevice 114 relative to the media exposure environment 102 enable theexample presence detector 212 of FIG. 5 to determine a presence of, forexample, the first person 120 in the media exposure environment 102. Forexample, if the example proximity determiner 504 of FIG. 5 determinesthat a person is in proximity to the portable device 114 and the examplelocation determiner 502 of FIG. 5 determines that the portable device114 is co-located with the primary media presentation device 104 (e.g.,is in the media exposure environment 102), then the first person 120 isdetermined to be present or located in the media exposure environment102.

In some such examples, where the primary presence data, according to theprimary people meter 112, indicates that at least one person is alreadycounted as present in the media exposure environment 102, there is apossibility that the portable device 114 is detecting the person that isalready accounted for via the primary people meter 112. As such,counting the person detected as present via the portable device 114 maybe duplicative.

Accordingly, in some examples, the presence detector 212 of FIG. 5includes the identity estimator 506 to estimate the identity of thedetected person in proximity to the portable device 114 to confirmwhether the detected person corresponds to the person logged in via theprimary people meter 112. In some examples, where there is only oneperson that resides in the house 100, the example identity estimator 506of FIG. 5 identifies that person as the single household member. In someexamples, when there is more than one household member (e.g., asillustrated by the first and second persons 120, 122 in FIG. 1), theexample identity estimator 506 of FIG. 5 determines or estimates theidentity of the detected person based on, for example, an identity ofthe primary user associated with the portable device 114. For example,if the portable device 114 is a smart phone primarily used by the personthat is currently logged in via the primary people meter 112, theexample identity estimator 506 of FIG. 5 determines that the detectedperson is the same as the logged in person. If, on the other hand, theportable device 114 is a smart phone primarily used by a spouse of theperson logged in as the audience member via the primary people meter112, the example identity estimator 506 of FIG. 5 estimates that theperson detected in proximity to the portable device 114 is the spouseand, therefore, is present in the media exposure environment 102 but hasnot logged in via the primary people meter 112. Example methods ofdetermining a number of people in an area (such as the media exposureenvironment 102) are disclosed in U.S. application Ser. No. 13/829,067filed on Mar. 14, 2013, which is hereby incorporated by reference in itsentirety.

In some examples, the portable device 114 may not be associated with aprimary user to confidently identify the detected person on that basis.For example, the first and second persons 120, 122 of FIG. 1 may share adevice (e.g., a tablet or laptop computer) such that there is noapparent primary user of the portable device 114. In such examples, theidentity estimator 506 of FIG. 5 assigns a probability or confidencelevel to each of the persons 120, 122 that they correspond to thedetected person based on, for example, one or more of the secondarypresence data obtained from the portable device 114. For instance, insome examples, the example identity estimator 506 of FIG. 5 analyzes theproximity information obtained from the proximity information generator404 of the portable device 114 to assist in identifying a persondetected in proximity to the portable device 114 to increase or decreasethe confidence that the detected person is one of the first or secondpersons 120, 122. For example, the identity estimator 506 of FIG. 5 usesvoice recognition technology to analyze audio data obtained via theaudio sensor 420 to specifically identify the voice of the detectedperson as corresponding to a particular one of the persons 120, 122. Insome examples, the captured audio data is compared against prerecordedvoice signatures for each of the persons 120, 122 to identify theparticular person 120, 122. In some examples, the captured audio data isanalyzed to recognize demographic characteristics (e.g., a male voiceversus a female voice) to be compared with the demographiccharacteristics of the persons 120, 122 previously collected as part of,for example, a registration process with the media measurement entity.Similarly, in some examples, the example identity estimator 506 of FIG.5 analyzes the image data (e.g., a picture and/or a video) from thecamera 424 of the example proximity information generator 404 of FIG. 4using facial recognition technology to compare against previouslycaptured images of the persons 120, 122 and/or to estimate demographicscharacteristics of the detected person corresponding to thecharacteristics of the persons 120, 122. In some examples, where thefingerprint reader 426 is used, the identity estimator 506 of FIG. 5positively identifies the detected person based on the uniqueness of theperson's fingerprint.

Additionally, in some examples, the particular applications and/or typesof applications being used on the portable device 114 and/or theactivity engaged in while using the applications may be used to estimatethe identity of the detected person. For example, if the detected personis using applications involving children's games and/or entertainmentfor children, the example identity estimator 506 of FIG. 5 estimates(e.g., increases the corresponding probability) that the detected personis a child and/or reduces the probability that the detected person is anadult. Further, if there is only one child that resides in the house100, the example identity estimator 506 of FIG. 5 significantlyincreases the confidence level that the person detected is the child ifa children's game or other activity is detected as in use on the device.In some examples, where the application usage is late at night, theexample identity estimator 506 of FIG. 5 reduces the probability thatthe detected person is a child and increases the probability that thedetected person is an adult. Further, some applications of the portabledevice 114 require a user authentication (e.g., a user account login)before operating. Accordingly, in some examples, the example identityestimator 506 of FIG. 5 identifies the person detected in proximity tothe portable device 114 as corresponding to a user associated with auser account of the application being used on the portable device 114(e.g., as detected by the application usage detector 428 of thesecondary data generator 400). In some examples, due to privacy and/orsecurity concerns, the actual user login information is unavailable tothe example application usage detector 428. However, in some suchexamples, the activity engaged in through the use of the applications ismonitored and linked back to the user account. For example, the personusing the portable device 114 may be participating in social media(e.g., Facebook®, Twitter®, Google+®, blogs, etc.) and may, for example,post a tweet (e.g., on Twitter®). Such an activity requires the personto be logged into the Twitter® account from which the tweet was posted.Accordingly, based on the data collected by the example applicationusage detector 428 of FIG. 4, the tweet can be sourced to the portabledevice 114 and, thus, the person using the portable device 114 can beidentified as corresponding to the user account from which the tweet wasposted.

In the illustrated example of FIG. 5, the identity estimator 506generates a probability or confidence level that any particular one ofthe persons 120, 122 associated with the house 100 corresponds to theperson detected as near the portable device 114. In some such examples,where the probability of one of the persons 120, 122 satisfies (e.g.,exceeds) a certain threshold and/or is larger than the probabilities ofthe other persons 120, 122, the example identity estimator 506 of FIG. 5identifies that one particular person 120, 122 as the person detected asnear the portable device 114. In some examples, if the probability ofcorrespondence between the detected person and each of the persons 120,122 is sufficiently low (e.g., below a threshold), the example identityestimator 506 identifies the detected person as likely corresponding toa visitor (e.g., not a resident of or a panelist residing at the house100). That is, the example identity estimator 506 of FIG. 5 identifiesthe detected person as a visitor to the house 100 (e.g., when theportable device 114 is located at the house 100), or identifies theperson as someone of no consequence to the media exposure environment102 (e.g., when the portable device 114 is determined to be located awayfrom the house 100). In some examples, the secondary presence datacollected by the portable device 114 indicates that more than one personis in proximity to the portable device 114. In such examples, theidentity estimator 506 of FIG. 5 analyzes each such person in a similarmanner as described above.

In some examples, where the example identity estimator 506 of FIG. 5identifies the person detected as proximate to the portable device 114as a visitor in the house 100, there is a desire to determinedemographic information about the visitor. As such, the example presencedetector 212 of FIG. 5 includes the characteristic estimator 508 toestimate demographic characteristics of the person in proximity to theportable device 114. The example characteristic estimator 508 of FIG. 5operates similarly to the example identity estimator 506 of FIG. 5. Theexample characteristic estimator 508 of FIG. 5 analyzes the proximityinformation generated by the proximity information generator 404 of theportable device 114 to estimate a demographic characteristic (e.g.,child/adult, male/female, etc.) of the person identified as not one ofthe persons 120, 122 associated with (e.g., a panelist of) the house100. In this manner, valuable information about visitors in panelisthomes can be obtained that would otherwise be unavailable because,although a traditional people meter may include a button to identify thepresence of visitors, there is no input for any other information aboutthe visitor.

The example presence detector 212 of FIG. 5 includes the presence datacomparator 510 to compare the primary presence data obtained via theprimary people meter 112 to the secondary presence data (e.g., locationof the portable device 114 and proximity of an identified person to theportable device 114) obtained via the portable device 114. In thismanner, the example presence data comparator 510 of FIG. 5 confirms thepresence of people logged into the primary people meter 112 and/orupdates, corrects, or adjusts the information gathered by the primarypeople meter 112. Because the presence information obtained from theportable device 114 is based on two variables (location of the portabledevice 114 and proximity of a person to the portable device 114)compared against the presence of people as determined based on loginstatus on the primary people meter 112, there are eight differentscenarios detected by the example presence data comparator 510 of FIG.5.

FIG. 6 is a table 600 that illustrates several possible scenarios602-616 and the corresponding determinations made by the examplepresence data comparator 510 of FIG. 5. A first column 618 of the table600 indicates whether a person is detected as being near the portabledevice 114 as determined based on proximity information collected by theportable device 114. A second column 620 of the table 600 indicateswhether the portable device 114 is located in the media exposureenvironment 102 as determined based on location information collected bythe portable device 114. A third column 622 of the table 600 indicatesthe presence of the person within the media exposure environment basedon data collected by the primary people meter 112 (e.g., whether theperson is logged in as present). A fourth column 624 of the tableindicates the result of the determination made by the example presencedata comparator 510 of FIG. 5 and used by the example presence detector212 for a conclusion regarding, for example, whether the first person120 is present in the media exposure environment 102.

As shown in the illustrated example of FIG. 6, the first four scenarios602, 604, 606, 608 correspond to when a person is not detected inproximity to the portable device 114. In some such examples, thelocation of the person cannot be verified based on the secondarypresence data because the location of the person cannot be linked to thelocation of the portable device 114. Accordingly, in some such examples,the example presence data comparator 510 of FIG. 5 ignores the presenceinformation obtained from the portable device 114 such that the outputpresence of the person (fourth column 624) corresponds to the presenceas determined by the primary people meter 112 (third column 622).However, in alternative scenarios, the example presence data comparator510 of FIG. 5 infers the absence of the person from the media exposureenvironment 102. For example, if the portable device 114 is located awayfrom the house 100, the example presence data comparator 510 of FIG. 5infers that, even if the portable device 114 does not detect a personnear the portable device 114, a person is likely not in the mediaexposure environment 102 because the portable device 114 is outside thehouse 100 and this is indicative of the corresponding person beingoutside of the house 100. Because there are other potentialexplanations, such as, the portable device 114 was left or lost at itsdetected location or is being carried by someone other than thecorresponding person 120, in some such examples, the presence datacomparator 510 of FIG. 5 merely flags the primary presence data recordedby the primary people meter 112 as suspect when the people meter 112indicates the person 120 is present (e.g., the second scenario 604).Alternatively, in some examples, if the portable device 114 is locatedin the media exposure environment 102 while no person is detected, theexample presence data comparator 510 of FIG. 5 flags the primarypresence data of the primary people meter 112 as suspect that indicatesthat a person is present (e.g., the fourth scenario 608).

In the four scenarios 610, 612, 614, 616 represented in the bottom rowsof the table 600 of FIG. 6, a person is detected by the portable device114 as being in proximity to the portable device 114. As such, thepresence of the person can be determined based on a determination of thelocation of the portable device 114. For example, in such scenarios, ifthe portable device 114 is located in the example media exposureenvironment 102, the presence of the person in the media exposureenvironment 102 may be inferred. By contrast, if the portable device 114is not located in the media exposure environment 102, the absence of theperson from the media exposure environment 102 may be inferred.Accordingly, in the fifth and eighth scenarios 610, 616 of the table 600of FIG. 6, the example presence data comparator 510 of FIG. 5 confirmsthe presence or absence of the person as indicated by the primary peoplemeter 112 because the portable device 114 is determined to be located ina location corresponding to the presence or absence of the person. Inthe sixth scenario 612 of the table 600 of FIG. 6, the portable device114 is located outside of the media exposure environment 102 such thatthe person (determined to be in proximity to the portable device 114) isalso outside the media exposure environment 102, but the primary peoplemeter 112 indicates that the person is present. In such an example, theexample presence data comparator 510 of FIG. 5 adjusts the correspondingdata to indicate the person is absent rather than present. In theseventh scenario 614 of the table 600 of FIG. 6, the location of theportable device 114 (and, thus, the location of the person due to thedetected proximity of the person) is determined to be within the mediaexposure environment 102, while the primary people meter 112 indicatesthe person is absent. In such an example, the example presence datacomparator 510 of FIG. 5 adjusts the corresponding to indicate theperson is present rather than absent.

In some examples, the scenarios of FIG. 6 described above, and theresulting output of the example presence data comparator 510 of FIG. 5is based on a known identity (e.g., up to a certain confidence level) ofthe detected person. Where the identity of the person cannot bepositively ascertained with sufficient certainty, in some examples,rather than adjusting the presence of registered audience members, theexample presence data comparator 510 of FIG. 5 flags the primarypresence data of the primary people meter 112 as suspect, indeterminate,and/or unconfirmed. In some examples, the presence data comparator 510of FIG. 5 makes certain determinations based on the information that isavailable even when detected person(s) are not identified. For example,if the number of people detected by the portable device 114 exceeds thenumber of people logged in via the primary people meter 112, then theexample presence data comparator 510 of FIG. 5 increases the total countof audience members without attributing the presence to any particularindividual (e.g., panelist).

The example presence detector 212 of FIG. 5 includes the activitydeterminer 512 to determine an activity or behavior of the persondetected via the portable device 114 based on, for example, movementdata obtained via one or more sensors 430 of the activity informationgenerator 406 of the portable device 114. For example, data from anaccelerometer and/or a magnetometer of the portable device 114 isanalyzed by the activity determiner 512 to determine whether the personis walking or sitting, playing a videogame, reading an e-book, browsingthe internet, etc. In some examples, the activity determiner 512 of FIG.5 associates the activity information of the person with other data(e.g., presence data, demographics data, media identifying information,etc.) to enhance or augment the data for further research analysis.

In the illustrated example of FIG. 5, the engagement determiner 514determines a level of engagement of the person with, for example, amedia presentation of the primary media presentation device 104 and/or amedia presentation of the portable device 114. In some examples, theengagement determiner 514 of FIG. 5 determines the level of engagementof the person with the media presentation based on the usage of one ormore programs or applications executing on the portable device 114, ascollected by, for example, the application usage detector 432 of theengagement information generator 408 of FIG. 4. In some examples, theengagement determiner 514 of FIG. 5 compares the subject matter of theusage of the portable device 114 to the subject matter or media of themedia presentation of the primary media presentation device 104. If thesubject matter of the application usage is related to the media (e.g., apost on Facebook® about the media presentation, a visit to a websiteassociated with the media presentation, an interaction with a secondscreen application, etc.), the engagement determiner 514 of FIG. 5determines a high level of engagement with the media. If, on the otherhand, the subject matter of the usage is unrelated to the media, theexample engagement determiner 514 of FIG. 5 determines a low level ofengagement with the media.

In some examples, the engagement determiner 514 of FIG. 5 determines thelevel of engagement of the person with the media based on the activityof the person determined via the activity determiner 512 and/or anadditional analysis of the activity information generated by theactivity information generator 406. For example, if the activityinformation indicates that the person is walking or moving within themedia exposure environment 102, the example engagement determiner 514 ofFIG. 5 determines a low level of engagement because the person is likelydistracted (e.g., is paying attention to something other than the mediapresented on the primary media presentation device 104). If the activityinformation indicates that the person is relatively still (e.g.,sitting), the example engagement determiner 514 of FIG. 5 determines ahigh level of engagement. If the activity information does not indicateany movement for an extended period of time (e.g., greater than athreshold), the example engagement determiner 514 of FIG. 5 determinesthat the person has likely fallen asleep and, thus, is no longer engagedin the media or has exited the room but left the portable device 114 inthe media exposure environment 102. Additional or alternative techniquesand/or interpretations of the activity data can be used to determine alevel of engagement of a person with a media presentation. Exampleengagement level determination techniques are disclosed in U.S. patentapplication Ser. No. 13/691,579 filed on Nov. 30, 2012 and in U.S.patent application Ser. No. 13/691,557 filed on Nov. 30, 2012, both ofwhich are hereby incorporated by reference in their entireties.

While an example manner of implementing the presence detector 212 ofFIGS. 2 and/or 4 is illustrated in FIG. 5, one or more of the elements,processes and/or devices illustrated in FIG. 5 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example location determiner 502, the example proximitydeterminer 504, the example identity estimator 506, the examplecharacteristic estimator 508, the example presence data comparator 510,the example activity determiner 514, the example engagement determiner514, and/or, more generally, the example presence detector 212 of FIG. 5may be implemented by hardware, software, firmware and/or anycombination of hardware, software and/or firmware. Thus, for example,any of the example location determiner 502, the example proximitydeterminer 504, the example identity estimator 506, the examplecharacteristic estimator 508, the example presence data comparator 510,the example activity determiner 514, the example engagement determiner514, and/or, more generally, the example presence detector 212 could beimplemented by one or more analog or digital circuit(s), logic circuits,programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example locationdeterminer 502, the example proximity determiner 504, the exampleidentity estimator 506, the example characteristic estimator 508, theexample presence data comparator 510, the example activity determiner514, and/or the example engagement determiner 514 is/are herebyexpressly defined to include a tangible computer readable storage deviceor storage disk such as a memory, a digital versatile disk (DVD), acompact disk (CD), a Blu-ray disk, etc. storing the software and/orfirmware. Further still, the example presence detector 212 of FIG. 5 mayinclude one or more elements, processes and/or devices in addition to,or instead of, those illustrated in FIG. 5, and/or may include more thanone of any or all of the illustrated elements, processes and devices.

A flowchart representative of example machine readable instructions forimplementing the example base metering device 110 of FIGS. 1 and/or 2 isshown in FIG. 7. A flowchart representative of example machine readableinstructions for implementing the example portable device 114 of FIGS. 1and/or 4 is shown in FIG. 8. A flowchart representative of examplemachine readable instructions for implementing the example presencedetector 212 of FIGS. 2, 4 and/or 5 is shown in FIGS. 9 and 10. In theseexamples, the machine readable instructions comprise a program forexecution by a processor such as the processor 1112 shown in the exampleprocessor platform 1100 discussed below in connection with FIG. 11. Theprogram may be embodied in software stored on a tangible computerreadable storage medium such as a CD-ROM, a floppy disk, a hard drive, adigital versatile disk (DVD), a Blu-ray disk, or a memory associatedwith the processor 1112, but the entire program and/or parts thereofcould alternatively be executed by a device other than the processor1112 and/or embodied in firmware or dedicated hardware. Further,although the example program is described with reference to theflowcharts illustrated in FIGS. 7-10, many other methods of implementingthe example base metering device 110, the example portable device 114,and/or the example presence detector 212 may alternatively be used. Forexample, the order of execution of the blocks may be changed, and/orsome of the blocks described may be changed, eliminated, or combined.

As mentioned above, the example processes of FIGS. 7-10 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals. As used herein, “tangible computerreadable storage medium” and “tangible machine readable storage medium”are used interchangeably. Additionally or alternatively, the exampleprocesses of FIGS. 7-10 may be implemented using coded instructions(e.g., computer and/or machine readable instructions) stored on anon-transitory computer and/or machine readable medium such as a harddisk drive, a flash memory, a read-only memory, a compact disk, adigital versatile disk, a cache, a random-access memory and/or any otherstorage device or storage disk in which information is stored for anyduration (e.g., for extended time periods, permanently, for briefinstances, for temporarily buffering, and/or for caching of theinformation). As used herein, the term non-transitory computer readablemedium is expressly defined to include any type of computer readabledevice or disk and to exclude propagating signals. As used herein, whenthe phrase “at least” is used as the transition term in a preamble of aclaim, it is open-ended in the same manner as the term “comprising” isopen ended.

The example of FIG. 7 begins at block 702 with the example mediadetector 202 of FIG. 2 collecting media identifying data from a primarymedia presentation device (e.g., the media presentation device 104 ofFIG. 1) of the media exposure environment 102 of FIG. 1. At block 704,the example time stamper 206 time stamps the media identifying data. Atblock 706, the example people analyzer 200 obtains primary presence datafrom the primary people meter 112 of FIG. 1. At block 708, the exampletime stamper 206 time stamps the primary presence data. At block 710,the people analyzer 200 obtains secondary presence data from a portabledevice (e.g., the first portable device 114 and/or the second portabledevice 118 of FIG. 1). In some examples, the secondary presence data iscollected in response to a control signal sent via a secondary datacoordinator (e.g., the secondary data coordinator 213 of FIG. 2). Atblock 712, the example presence detector 212 of FIG. 2 analyzes comparesthe primary presence data and collected by the primary people meter 112and the secondary presence data collected by the portable device(s) 114,118. An example implementation of block 712 is described below inconnection with FIGS. 9 and 10. At block 714, the example output device214 of FIG. 2 transmits resulting media measurement data to the datacollection facility 216 as described above in connection with FIG. 2.

The example of FIG. 8 begins at block 802 with the example locationinformation generator 402 of FIG. 4 generates location informationindicative of a location of, for example, the portable device 114. Atblock 804, the example proximity information generator 404 of FIG. 4generates proximity information indicative of one or more persons beingnear the portable device 114. At block 806, the example activityinformation generator 406 of FIG. 4 generates activity informationindicative of one or more user interactions with the portable device114. At block 808, the example engagement information generator 408 ofFIG. 4 generates engagement information indicative of one or more levelsof engagement with, for example, media playing on the primary mediapresentation device of the environment 102. At block 810, the exampletime stamper 410 time stamps the generated information (e.g., thelocation information generated at block 802, the proximity informationgenerated at block 804, the activity information generated at block 806,and the engagement information generated at block 808). At block 812,the example media detector 434 of FIG. 4 collects media identifying datafrom, for example, the primary media presentation device (e.g., theprimary media presentation device 104 of FIG. 1) of the media exposureenvironment 102. At block 814, the example time stamper 410 time stampsthe media identifying data. At block 816, the example presence detector412 of FIG. 4 collects primary presence data from the primary peoplemeter 112 via, for example, the base metering device 110 of FIG. 1. Atblock 818, the presence detector 412 of FIG. 4 compares the primarypresence data collected by the primary people meter 112 and thesecondary presence data collected by the portable device 114. An exampleimplementation of block 818 is described below in connection with FIGS.9 and 10. At block 820, the example output device 436 of FIG. 4transmits resulting media measurement data to the data collectionfacility 216.

FIG. 9 is an example implementation of block 712 of FIG. 7 and/or block818 of FIG. 8. The example of FIG. 9 begins at block 904 with theexample location determiner 502 of FIG. 5 determining the location of,for example, the first portable device 114 of FIG. 1. At block 906, theexample proximity determiner 504 of FIG. 5 determines whether a personis detected in proximity to the portable device 114. If no person isdetected in proximity to the portable device 114, the example of FIG. 9ends. However, if a person is detected in proximity to the portabledevice 114, control advances to block 908 and the example identityestimator 506 of FIG. 5 determines whether the person is identified as apanelist (e.g., the first person 120 of FIG. 1 or the second person 122of FIG. 1). If the example identity estimator 506 of FIG. 5 determinesthat the person is a panelist, control advances to block 910.

At block 910, the example location determiner 502 of FIG. 5 determineswhether the portable device 114 is located in the media exposureenvironment 102 of FIG. 1. If the example proximity determiner 504 ofFIG. 5 determines that the portable device 114 is located in the mediaexposure environment 102, control advances to block 912 where theexample presence data comparator 510 of FIG. 5 determines whether thedetected person is logged in via the primary people meter 112. In someexamples, the presence data comparator 510 of FIG. 5 makes such adetermination by comparing the identified person to the people logged inon the primary people meter 112 as indicated (e.g., according to theprimary presence data tracked in the presence table 210 of FIG. 2). Ifthe example presence data comparator 510 of FIG. 5 determines that theperson is not logged in on the primary people meter 112, controladvances to block 914 where the example presence data comparator 510 ofFIG. 5 updates the primary presence data in accordance with theadditional person indication. At block 916, the example activitydeterminer 512 of FIG. 5 and the example engagement determiner 514 ofFIG. 5 associate secondary data (e.g., augmented audience data) with themedia measurement data, as described below in connection with FIG. 10.If the example presence data comparator 510 of FIG. 5 determines thatthe person is logged in on the primary people meter 112 (block 912),control advances to block 916. That is, the example presence datacomparator 510 of FIG. 5 does not update the primary presence data(block 914) because the person identified via the secondary presencedata is already accounted for by the primary presence data. When thesecondary data is associated with the media measurement data (block916), the example of FIG. 9 ends.

At block 910, if the example location determiner 502 of FIG. 5determines that the portable device 114 is not located in the mediaexposure environment 102, control advances to block 918 where theexample presence data comparator 510 of FIG. 5 determines whether theperson is logged in via the primary people meter 112 in a similar manneras described above with respect to block 912. If the example presencedata comparator 510 of FIG. 5 determines that the person is logged invia the primary people meter 112, control advances to block 920 wherethe example presence data comparator 510 of FIG. 5 updates the primarypresence data to remove the incorrectly identified person. That is, thepresence information according to the person being logged-in (accordingto the primary presence data) is incorrect because the secondarypresence data confirms that the person is away from (e.g., not locatedin) the media exposure environment 102. The example of FIG. 9 then ends.If the example presence data comparator 510 of FIG. 5 determines thatthe person is not logged in via the primary people meter 112 (block918), the example of FIG. 9 ends because there is no relevantinformation to update because the location of the person being away fromthe media exposure environment 102 is in agreement with the loggedstatus of the person according to the primary people meter 112 (i.e.,not logged in).

At block 908, if the example identity estimator 506 of FIG. 5 determinesthat the person is not identified as a panelist (e.g., the person is aguest or visitor), control advances to block 922 where the examplelocation determiner 502 of FIG. 5 determines whether the portable device114 is located in the media exposure environment 102 in a similar manneras described above in connection with block 910. If the example locationdeterminer 502 of FIG. 5 determines that the portable device 114 islocated in the media exposure environment 102, control advances to block924 where the example characteristic estimator 508 of FIG. 5 identifiesor estimates at least one demographic characteristic of the person.

At block 926, the example presence data comparator 510 of FIG. 5determines whether the person is logged in via the primary people meter112. In some examples, when the identity estimator 506 of FIG. 5determines that the person is not a panelist (block 908) but thedetected person is present in the media exposure environment 102, theexample presence data comparator 510 of FIG. 5 assumes that the personis a visitor or guest in the house 100. Accordingly, in some examples,the example presence data comparator 510 of FIG. 5 determines whetherthe person is logged in based on whether inputs into the primary peoplemeter 112 indicate a visitor is viewing the primary media presentationdevice. If the example presence data comparator 510 of FIG. 5 determinesthat the person is logged in via the primary people meter 112, controladvances to block 928 where the example presence data comparator 510 ofFIG. 5 associates one or more demographic characteristics with thelogged-in person before advancing to block 916. If the example presencedata comparator 510 of FIG. 5 determines that the person is not loggedvia the primary people meter 112, control advances to block 914 wherethe presence data comparator 510 of FIG. 5 updates the primary presencedata to indicate the presence of the person. In some such examples, thepresence data comparator 510 of FIG. 5 updates the primary presence dataand associates the one or more demographic characteristics with theadded person. Returning to block 922, if the example location determiner502 of FIG. 5 determines that the portable device 114 is not located inthe media exposure environment, the example of FIG. 9 ends because noreliable conclusions are to be drawn based on a detected person thatcannot be identified as a panelist (block 908) and is not located in themedia exposure environment 102 (block 922).

FIG. 10 is a flow diagram representative of example machine readableinstructions that may be executed to implement block 916 of the exampleof FIG. 9. The example of FIG. 10 begins at block 1002 with the exampleactivity determiner 512 of FIG. 5 determining an activity of thedetected person. At block 1004, the example engagement determiner 514 ofFIG. 5 determines a level of engagement of the person with the mediapresentation. At block 1006, the example activity determiner 512 of FIG.5 associates the determined activity with the media measurement datacorresponding to the person. At block 1008, the example engagementdeterminer of FIG. 5 associates the level of engagement of the personwith the media measurement data corresponding to the person. In thismanner, in addition to the media measurement data indicative of a numberof audience members and/or the corresponding demographic information,the media measurement data is augmented with additional information thatmay give a media measurement entity greater insight into the audience ofa particular media presentation.

FIG. 11 is a block diagram of an example processor platform 1100 capableof executing the instructions of FIG. 7 to implement the base meteringdevice 110 of FIGS. 1 and/or 2, capable of executing the instructions ofFIG. 8 to implement the portable device(s) 114, 118 of FIGS. 1 and/or 4,and/or capable of executing the instructions of FIGS. 9 and 10 toimplement the presence detector 212 of FIGS. 2, 4 and/or 5. Theprocessor platform 1100 can be, for example, a server, a personalcomputer, a mobile device (e.g., a cell phone, a smart phone, a tabletsuch as an iPad™), a personal digital assistant (PDA), an Internetappliance, a DVD player, a CD player, a digital video recorder, aBlu-ray player, a gaming console, a personal video recorder, a set topbox, or any other type of computing device.

The processor platform 1100 of the illustrated example includes aprocessor 1112. The processor 1112 of the illustrated example ishardware. For example, the processor 1112 can be implemented by one ormore integrated circuits, logic circuits, microprocessors or controllersfrom any desired family or manufacturer.

The processor 1112 of the illustrated example includes a local memory1113 (e.g., a cache). The processor 1112 of the illustrated example isin communication with a main memory including a volatile memory 1114 anda non-volatile memory 1116 via a bus 1118. The volatile memory 1114 maybe implemented by Synchronous Dynamic Random Access Memory (SDRAM),Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory(RDRAM) and/or any other type of random access memory device. Thenon-volatile memory 1116 may be implemented by flash memory and/or anyother desired type of memory device. Access to the main memory 1114,1116 is controlled by a memory controller.

The processor platform 1100 of the illustrated example also includes aninterface circuit 1120. The interface circuit 1120 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 1122 are connectedto the interface circuit 1120. The input device(s) 1122 permit(s) a userto enter data and commands into the processor 1112. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 1124 are also connected to the interfacecircuit 1120 of the illustrated example. The output devices 1124 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a light emitting diode (LED), a printer and/or speakers).The interface circuit 1120 of the illustrated example, thus, typicallyincludes a graphics driver card, a graphics driver chip or a graphicsdriver processor.

The interface circuit 1120 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network1126 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 1100 of the illustrated example also includes oneor more mass storage devices 1128 for storing software and/or data.Examples of such mass storage devices 1128 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

The coded instructions 1132 of FIGS. 7-10 may be stored in the massstorage device 1128, in the volatile memory 1114, in the non-volatilememory 1116, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

1. A method comprising: analyzing location information collected by aportable device indicative of a location of the portable device;analyzing proximity information collected by the portable deviceindicative of a person being near the portable device; and generatingfirst presence information based on (1) the location information and (2)the proximity information, the presence information indicative ofwhether the person is present in a media exposure environment associatedwith a media presentation device.
 2. A method as defined in claim 1,further comprising comparing the first presence information to secondpresence information collected via a people meter associated with themedia presentation device.
 3. A method as defined in claim 2, whereinthe second presence information is generated based on manual inputs tothe people meter.
 4. A method as defined in claim 2, further comprisingadjusting the second presence information based on the comparison.
 5. Amethod as defined in claim 2, further comprising adjusting the secondpresence information by increasing a people count when the person doesnot correspond to any person logged in to the people meter and the firstpresence information indicates the person is present in the mediaexposure environment.
 6. A method as defined in claim 2, furthercomprising adjusting the second presence information by decreasing apeople count when the person corresponds to a person logged in to thebase meter and the first presence information indicates the person isabsent from the media exposure environment.
 7. A method as defined inclaim 1, further comprising: if the location of the portable device iswithin the media exposure environment, determining that the person ispresent in the media exposure environment when the person is near theportable device; and if the location of the portable device is outsidethe media exposure environment, determining that the person is absentfrom the media exposure environment when the person is near the portabledevice.
 8. A method as defined in claim 1, wherein the proximityinformation is based on usage information indicative of usage of anapplication executing on the portable device.
 9. A method as defined inclaim 8, further comprising estimating at least one of an identity ofthe person or a demographic characteristic of the person based on a typeof the application executing on the portable device.
 10. A method asdefined in claim 8, further comprising identifying the person based on auser account associated with the application, the usage of theapplication involving the person logging in to the user account.
 11. Amethod as defined in claim 1, further comprising transmitting a controlsignal to the portable device requesting the location information andthe proximity information from the portable device.
 12. An apparatuscomprising: a location determiner to determine a location of a portabledevice based on location information generated by the portable device; aproximity determiner to determine that a person is in proximity to theportable device based on data collected by the portable device; and apresence detector to generate first presence information based on (1)the location of the portable device and (2) the proximity of the personto the portable device, the first presence information indicative ofwhether the person is present in a media exposure environment associatedwith a media presentation device.
 13. An apparatus as defined claim 12,wherein the presence detector is to: compare the first presenceinformation to second presence data collected via a people meter locatedin the media exposure environment; and adjust the second presence databased on the comparison.
 14. (canceled)
 15. (canceled)
 16. An apparatusas defined in claim 12, wherein the presence detector is to: if thelocation of the portable device is within the media exposureenvironment, determine that the person is present in the media exposureenvironment when the person is in proximity to the portable device; andif the location of the portable device is outside the media exposureenvironment, determine that the person is absent from the media exposureenvironment when the person is in proximity to the portable device. 17.An apparatus as defined in claim 12, wherein the proximity informationis based on usage information indicative of usage of an applicationexecuting on the portable device.
 18. An apparatus as defined in claim17, further comprising an identity estimator to estimate an identity ofthe person based on a type of the application executing on the portabledevice.
 19. An apparatus as defined in claim 17, further comprising acharacteristic estimator to estimate a demographic characteristic of theperson based on a type of the application executing on the portabledevice.
 20. An apparatus as defined in claim 17, further comprising anidentity estimator to identify the person based on a user accountassociated with the application, the usage of the application involvingthe person logging in to the user account.
 21. An apparatus as definedin claim 12, wherein the portable device and the media presentationdevice are associated with a panelist of a media measurement panel. 22.An apparatus as defined in claim 21, wherein the person is not thepanelist.
 23. An apparatus as defined in claim 12, further comprising adata coordinator to trigger the collection of data by the portabledevice.
 24. A tangible machine readable storage medium havinginstructions stored thereon that, when executed, cause a machine to atleast: detect a location of a portable device based on locationinformation generated by the portable device; detect when a person is inproximity to the portable device based on proximity informationgenerated by the portable device; and generate first presenceinformation based on (1) the location of the portable device and (2) theproximity of the person to the portable device, the first presenceinformation indicative of whether the person is present in a mediaexposure environment including a media presentation device.
 25. Astorage medium as defined in claim 24, wherein the instructions causethe machine to compare the first presence information to second presenceinformation collected via a people meter associated with the mediapresentation device, the second presence information being based onmanual inputs to the people meter.
 26. A storage medium as defined inclaim 25, wherein the instructions cause the machine to adjust thesecond presence information based on the comparison.
 27. A storagemedium as defined in claim 26, wherein the instructions cause themachine to adjust the second presence information by adding the personto a record of people detected in the media exposure environment whenthe person does not correspond to any person logged in via the peoplemeter and the first presence information indicates the person is presentin the media exposure environment.
 28. A storage medium as defined inclaim 26, wherein the instructions cause the machine to adjust thesecond presence information by removing the person from a record ofpeople detected in the media exposure environment when the personcorresponds to a person logged in via the people meter and the firstpresence information indicates the person is absent from the mediaexposure environment.
 29. (canceled)
 30. A storage medium as defined inclaim 24, wherein the proximity information is based on usageinformation indicative of usage of an application executing on theportable device.
 31. (canceled)
 32. (canceled)
 33. A storage medium asdefined in claim 30, wherein the instructions cause the machine toidentify the person based on a user account associated with theapplication, the usage of the application involving the person loggingin to the user account.
 34. A storage medium as defined in claim 24,wherein the instructions cause the machine to trigger collection of thelocation information and the proximity information by the portabledevice. 35.-49. (canceled)